METHODS: Using HPV serology as a marker of HPV-related cancer, we examined the interaction between smoking and HPV16 in 459 oropharyngeal (and 1445 oral cavity and laryngeal) cancer patients and 3024 control participants from two large European multi-centre studies. Odds ratios and credible intervals [CrI], adjusted for potential confounders, were estimated using Bayesian logistic regression.
RESULTS: Both smoking [odds ratio (OR [CrI]: 6.82 [4.52, 10.29]) and HPV seropositivity (OR [CrI]: 235.69 [99.95, 555.74]) were independently associated with oropharyngeal cancer. The joint association of smoking and HPV seropositivity was consistent with that expected on the additive scale (synergy index [CrI]: 1.32 [0.51, 3.45]), suggesting they act as independent risk factors for oropharyngeal cancer.
CONCLUSIONS: Smoking was consistently associated with increase in oropharyngeal cancer risk in models stratified by HPV16 seropositivity. In addition, we report that the prevalence of oropharyngeal cancer increases with smoking for both HPV16-positive and HPV16-negative persons. The impact of smoking on HPV16-positive oropharyngeal cancer highlights the continued need for smoking cessation programmes for primary prevention of head and neck cancer.
RESULTS: The spatial model with split random effects and a common intercept has the lowest Deviance and Watanabe Information Criteria. There was evidence of a spatial pattern in the prevalence of childhood overweight across districts. An increasing trend in smoothed prevalence of overweight was observed when moving from the east to the west of the Peninsular and Borneo regions. The proportion of Bumiputera ethnicity in the district had a significant negative association with childhood overweight: the higher the proportion of Bumiputera ethnicity in the district, the lower the prevalence of childhood overweight.
CONCLUSION: This study illustrates different available techniques for mapping prevalence across districts in disconnected regions using survey data. These techniques can be utilized to produce reliable subnational estimates for any areas that comprise of disconnected regions. Through the example, we learned that the best-fit model was the one that considered the separate variations of the individual regions. We discovered that the occurrence of childhood overweight in Malaysia followed a spatial pattern with an east-west gradient trend, and we identified districts with high prevalence of overweight. This information could help policy makers in making informed decisions for targeted public health interventions in high-risk areas.
METHODS: We conducted molecular detection, genetic characterization, and Bayesian time-scale evolution analyses of NiV using pooled Pteropid bat roost urine samples from an outbreak area in 2012 and archived RNA samples from NiV case patients identified during 2012-2018 in Bangladesh.
RESULTS: NiV-RNA was detected in 19% (38/456) of bat roost urine samples and among them; nine N gene sequences were recovered. We also retrieved sequences from 53% (21 out of 39) of archived RNA samples from patients. Phylogenetic analysis revealed that all Bangladeshi strains belonged to NiV-BD genotype and had an evolutionary rate of 4.64 × 10-4 substitutions/site/year. The analyses suggested that the strains of NiV-BD genotype diverged during 1995 and formed two sublineages.
CONCLUSION: This analysis provides further evidence that the NiV strains of the Malaysian and Bangladesh genotypes diverged recently and continue to evolve. More extensive surveillance of NiV in bats and human will be helpful to explore strain diversity and virulence potential to infect humans through direct or person-to-person virus transmission.
Methods: A total of 7180 STEMI male patients from the National Cardiovascular Disease Database-Acute Coronary Syndrome (NCVD-ACS) registry for the years 2006-2013 were enrolled. In the development of univariate and multivariate logistic regression model for the STEMI patients, Bayesian Markov Chain Monte Carlo (MCMC) simulation approach was applied. The performance of the model was assessed through convergence diagnostics, overall model fit, model calibration and discrimination.
Results: A set of six risk factors for cardiovascular death among STEMI male patients were identified from the Bayesian multivariate logistic model namely age, diabetes mellitus, family history of CVD, Killip class, chronic lung disease and renal disease respectively. Overall model fit, model calibration and discrimination were considered good for the proposed model.
Conclusion: Bayesian risk prediction model for CVD male patients identified six risk factors associated with mortality. Among the highest risks were Killip class (OR=18.0), renal disease (2.46) and age group (OR=2.43) respectively.
OBJECTIVE: To determine levels and trends in the fatal and nonfatal burden of diseases and injuries among younger children (aged <5 years), older children (aged 5-9 years), and adolescents (aged 10-19 years) between 1990 and 2013 in 188 countries from the Global Burden of Disease (GBD) 2013 study.
EVIDENCE REVIEW: Data from vital registration, verbal autopsy studies, maternal and child death surveillance, and other sources covering 14,244 site-years (ie, years of cause of death data by geography) from 1980 through 2013 were used to estimate cause-specific mortality. Data from 35,620 epidemiological sources were used to estimate the prevalence of the diseases and sequelae in the GBD 2013 study. Cause-specific mortality for most causes was estimated using the Cause of Death Ensemble Model strategy. For some infectious diseases (eg, HIV infection/AIDS, measles, hepatitis B) where the disease process is complex or the cause of death data were insufficient or unavailable, we used natural history models. For most nonfatal health outcomes, DisMod-MR 2.0, a Bayesian metaregression tool, was used to meta-analyze the epidemiological data to generate prevalence estimates.
FINDINGS: Of the 7.7 (95% uncertainty interval [UI], 7.4-8.1) million deaths among children and adolescents globally in 2013, 6.28 million occurred among younger children, 0.48 million among older children, and 0.97 million among adolescents. In 2013, the leading causes of death were lower respiratory tract infections among younger children (905.059 deaths; 95% UI, 810,304-998,125), diarrheal diseases among older children (38,325 deaths; 95% UI, 30,365-47,678), and road injuries among adolescents (115,186 deaths; 95% UI, 105,185-124,870). Iron deficiency anemia was the leading cause of years lived with disability among children and adolescents, affecting 619 (95% UI, 618-621) million in 2013. Large between-country variations exist in mortality from leading causes among children and adolescents. Countries with rapid declines in all-cause mortality between 1990 and 2013 also experienced large declines in most leading causes of death, whereas countries with the slowest declines had stagnant or increasing trends in the leading causes of death. In 2013, Nigeria had a 12% global share of deaths from lower respiratory tract infections and a 38% global share of deaths from malaria. India had 33% of the world's deaths from neonatal encephalopathy. Half of the world's diarrheal deaths among children and adolescents occurred in just 5 countries: India, Democratic Republic of the Congo, Pakistan, Nigeria, and Ethiopia.
CONCLUSIONS AND RELEVANCE: Understanding the levels and trends of the leading causes of death and disability among children and adolescents is critical to guide investment and inform policies. Monitoring these trends over time is also key to understanding where interventions are having an impact. Proven interventions exist to prevent or treat the leading causes of unnecessary death and disability among children and adolescents. The findings presented here show that these are underused and give guidance to policy makers in countries where more attention is needed.
METHODS: MEDLINE and Embase databases were searched from inception up to September 2019 to identify all studies that compared the predictive performance of cystatin C- and/or creatinine-based eGFR in predicting the clearance of vancomycin. The prediction errors (PEs) (the value of eGFR equations minus vancomycin clearance) were quantified for each equation and were pooled using a random-effects model. The root mean squared errors were also quantified to provide a metric for imprecision.
RESULTS: This meta-analysis included evaluations of seven different cystatin C- and creatinine-based eGFR equations in total from 26 studies and 1,234 patients. The mean PE (MPE) for cystatin C-based eGFR was 4.378 mL min-1 (95% confidence interval [CI], -29.425, 38.181), while the creatinine-based eGFR provided an MPE of 27.617 mL min-1 (95% CI, 8.675, 46.560) in predicting clearance of vancomycin. This indicates the presence of unbiased results in vancomycin clearance prediction by the cystatin C-based eGFR equations. Meanwhile, creatinine-based eGFR equations demonstrated a statistically significant positive bias in vancomycin clearance prediction.
CONCLUSION: Cystatin C-based eGFR equations are better than creatinine-based eGFR equations in predicting the clearance of vancomycin. This suggests that utilising cystatin C-based eGFR equations could result in better accuracy and precision to predict vancomycin pharmacokinetic parameters.
METHODS: Twenty-seven adolescents with OCD and 46 controls completed a predictive-inference task, designed to probe how subjects' actions and confidence ratings fluctuate in response to unexpected outcomes. We investigated how subjects update actions in response to prediction errors (indexing mismatches between expectations and outcomes) and used parameters from a Bayesian model to predict how confidence and action evolve over time. Confidence-action association strength was assessed using a regression model. We also investigated the effects of serotonergic medication.
RESULTS: Adolescents with OCD showed significantly increased learning rates, particularly following small prediction errors. Results were driven primarily by unmedicated patients. Confidence ratings appeared equivalent between groups, although model-based analysis revealed that patients' confidence was less affected by prediction errors compared to controls. Patients and controls did not differ in the extent to which they updated actions and confidence in tandem.
CONCLUSIONS: Adolescents with OCD showed enhanced action adjustments, especially in the face of small prediction errors, consistent with previous research establishing 'just-right' compulsions, enhanced error-related negativity, and greater decision uncertainty in paediatric-OCD. These tendencies were ameliorated in patients receiving serotonergic medication, emphasising the importance of early intervention in preventing disorder-related cognitive deficits. Confidence ratings were equivalent between young patients and controls, mirroring findings in adult OCD research.